đ Qwen/QwQ-32B - GGUF
This repo offers GGUF format model files for Qwen/QwQ-32B. It provides a convenient way to use the model with compatibility and quantization support.
đ Quick Start
This section provides a quick overview of the project and how to get started.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4823.
⨠Features
Our projects
đ Documentation
Prompt template
<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
<think>
Model file specification
Filename |
Quant type |
File Size |
Description |
QwQ-32B-Q2_K.gguf |
Q2_K |
12.313 GB |
smallest, significant quality loss - not recommended for most purposes |
QwQ-32B-Q3_K_S.gguf |
Q3_K_S |
14.392 GB |
very small, high quality loss |
QwQ-32B-Q3_K_M.gguf |
Q3_K_M |
15.935 GB |
very small, high quality loss |
QwQ-32B-Q3_K_L.gguf |
Q3_K_L |
17.247 GB |
small, substantial quality loss |
QwQ-32B-Q4_0.gguf |
Q4_0 |
18.640 GB |
legacy; small, very high quality loss - prefer using Q3_K_M |
QwQ-32B-Q4_K_S.gguf |
Q4_K_S |
18.784 GB |
small, greater quality loss |
QwQ-32B-Q4_K_M.gguf |
Q4_K_M |
19.851 GB |
medium, balanced quality - recommended |
QwQ-32B-Q5_0.gguf |
Q5_0 |
22.638 GB |
legacy; medium, balanced quality - prefer using Q4_K_M |
QwQ-32B-Q5_K_S.gguf |
Q5_K_S |
22.638 GB |
large, low quality loss - recommended |
QwQ-32B-Q5_K_M.gguf |
Q5_K_M |
23.262 GB |
large, very low quality loss - recommended |
QwQ-32B-Q6_K.gguf |
Q6_K |
26.886 GB |
very large, extremely low quality loss |
QwQ-32B-Q8_0.gguf |
Q8_0 |
34.821 GB |
very large, extremely low quality loss - not recommended |
đĻ Installation
Downloading instruction
Command line
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, download the individual model file to a local directory
huggingface-cli download tensorblock/QwQ-32B-GGUF --include "QwQ-32B-Q2_K.gguf" --local-dir MY_LOCAL_DIR
If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf
), you can try:
huggingface-cli download tensorblock/QwQ-32B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
đ License
This project is licensed under the Apache-2.0 License.